Method of monitoring health conditions of a patient having an implantable blood pump

ABSTRACT

A method of predicting an adverse event in a patient having an implantable blood pump including correlating a pulsatility value to a flow trough value associated with the blood pump to determine a flow peak value; dividing the determined flow peak value by a pump current to determine a pulsatility peak value; tracking a first moving average of the pulsatility peak value, the first moving average defining a threshold range; tracking a second moving average of the pulsatility peak value, the second moving average being faster than the first moving average; and generating an alert when the second moving average deviates from the threshold range.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Application Ser. No.62/816,957, filed Mar. 12, 2019.

FIELD

The present technology is generally related to an implantable bloodpump.

BACKGROUND

Mechanical circulatory support devices, such as implantable blood pumps,are used to assist the pumping action of a failing heart. Such bloodpumps may include a housing with an inlet, an outlet, and a rotormounted within the housing. The inlet may be connected to a chamber of apatient's heart, for example the left ventricle, using an inflowcannula. The outlet may be connected to an artery, such as the aorta.Rotation of the rotor drives blood from the inlet towards the outlet andthus assists blood flow from the chamber of the heart into the artery.

Known blood pumps are susceptible to experiencing adverse events whichmay result in costly hospitalizations and medical interventions forpatients. For example, whether systemic or cardio-pulmonary in nature,adverse events can impact ventricular volume and pressure which isreflected in pump parameters such as power, flow, current, speed, and/orderivatives of pump parameters, such as a patient's circadian cycle,heart rate, aortic valve status, and suction burden. Pump parametersobtained in real time may indicate an adverse event, but do not providean analysis of changes in pump parameters over time which may be usefulin identifying changes in a patient's health condition.

SUMMARY

The techniques of this disclosure generally relate to analyzing healthconditions of patients having an implantable blood pump and providing analert associated with negative health conditions.

In one aspect, the present disclosure provides a method of predicting anadverse event in a patient having an implantable blood pump includingcorrelating a pulsatility value to a flow trough value associated withthe blood pump to determine a flow peak value; dividing the determinedflow peak value by a pump current to determine a pulsatility peak value;tracking a first moving average of the pulsatility peak value, the firstmoving average defining a threshold range; tracking a second movingaverage of the pulsatility peak value, the second moving average beingfaster than the first moving average; and generating an alert when thesecond moving average deviates from the threshold range.

In another aspect, the disclosure provides recording a plurality ofalert occurrences over a time period, and based on the plurality ofalert occurrences, determining a risk factor associated with a predictedonset of the adverse event.

In another aspect, the disclosure provides based on the determined riskfactor, automatically classifying a patient's physiological state amonga ranking system.

In another aspect, the disclosure provides determining a standarddeviation of the first moving average, the first moving average and thestandard deviation defining the threshold range.

In another aspect, the disclosure provides the first moving averagebeing a twenty-four-hour moving average and the second moving averagebeing approximately a two-hour duration.

In one aspect, the present disclosure provides a system of predicting anadverse event in a patient having an implantable blood pump includingthe blood pump and a processor in communication with the blood pump, theprocessor having process circuitry configured to correlate a pulsatilityvalue to a flow trough value associated with the blood pump to determinea flow peak value; divide the determined flow peak value by a pumpcurrent to determine a pulsatility peak value; track a first movingaverage of the pulsatility peak value, the first moving average defininga threshold range; track a second moving average of the pulsatility peakvalue, the second moving average being faster than the first movingaverage; and generate an alert when the second moving average deviatesfrom the threshold range.

In another aspect, the disclosure provides the system including theprocess circuitry being configured to record a plurality of alertoccurrences over a time period, and based on the plurality of alertoccurrences, determine a risk factor associated with a predicted onsetof the adverse event.

In one aspect, the present disclosure provides a method of predicting anadverse event in a patient having an implantable blood pump includingtracking an average pulsatility value associated with the blood pump;tracking a plurality of parameters associated with the blood pumpincluding an average flow trough value, an average flow value, and astandard flow trough deviation value, the standard flow trough deviationvalue being measured with respect to the average flow trough value;correlating the average pulsatility value to the plurality ofparameters; determining an adverse event index value using thecorrelated average pulsatility value relative to the plurality ofparameters; comparing the adverse event index value to a predeterminedthreshold range; and generating an alert when the compared adverse eventindex value deviates from the predetermined threshold range.

In another aspect, the disclosure provides correlating the averagepulsatility value to a scaling coefficient.

In another aspect, the disclosure provides correlating the standard flowtrough deviation value to an offset value.

In another aspect, the disclosure provides determining a plurality ofadverse event index values during a plurality of time periods, comparingthe plurality of adverse event index values to each other, and based onthe compared plurality of adverse event index values, classifying apatient's physiological state among a ranking system.

In another aspect, the disclosure provides the average pulsatility valueand the plurality of parameters associated with the blood pump beingexpressed as a waveform, and the adverse event index value exceeding thepredetermined threshold range is expressed as an abnormal feature of thewaveform.

In one aspect, the present disclosure provides a system of predicting anadverse event in a patient having an implantable blood pump includingthe blood pump; and a processor in communication with the blood pump,the processor having process circuitry configured to track an averagepulsatility value associated with the blood pump; track a plurality ofparameters associated with the blood pump including an average flowtrough value, an average flow value, and a standard flow troughdeviation value, the standard flow trough deviation value being measuredwith respect to the average flow trough value; correlate the averagepulsatility value to the plurality of parameters; determine an adverseevent index value using the correlated average pulsatility valuerelative to the plurality of parameters; compare the adverse event indexvalue to a predetermined threshold range; and generate an alert when thecompared adverse event index value deviates from the predeterminedthreshold range.

In one aspect, the present disclosure provides a method of predicting anadverse event in a patient having an implantable blood pump includingidentifying a flow trough value associated with the blood pump duringuse; comparing the flow trough value to a standard deviation flow valueand an average flow value; determining a flow trough index value usingthe compared flow trough value to the standard deviation flow value andthe average flow value; and generating an alert when the flow troughindex value deviates from a predetermined threshold range.

In another aspect, the disclosure provides the based on the determinedflow trough index value, quantifying a suction prevalence associatedwith the blood pump.

In another aspect, the disclosure provides determining a plurality offlow trough index values, and based on the determined plurality of flowtrough index values, quantifying a suction prevalence associated withthe blood pump.

In another aspect, the disclosure provides the based on the suctionprevalence, classifying a patient's physiological state among a rankingsystem.

In another aspect, the disclosure provides the determining a presence ofa negative flow trough value relative to a flow scale, if the negativeflow trough value is present, correlating the flow trough value to aconstant, and following the correlated flow trough value to theconstant, determining the flow trough index value.

In another aspect, the disclosure provides multiplying the flow troughindex value by a corrective factor.

In another aspect, the disclosure provides the dividing the standarddeviation flow value and the average flow value.

In one aspect, the present disclosure provides a system of predicting anadverse event in a patient having an implantable blood pump includingthe blood pump; and a processor in communication with the blood pump,the processor having process circuitry configured to identify a flowtrough value associated with the blood pump during use; compare the flowtrough value to a standard deviation flow value and an average flowvalue; determine a flow trough index value using the compared flowtrough value to the standard deviation flow value and the average flowvalue; and generate an alert when the flow trough index value deviatesfrom a predetermined threshold range.

The details of one or more aspects of the disclosure are set forth inthe accompanying drawings and the description below. Other features,objects, and advantages of the techniques described in this disclosurewill be apparent from the description and drawings, and from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete understanding of the present invention, and theattendant advantages and features thereof, will be more readilyunderstood by reference to the following detailed description whenconsidered in conjunction with the accompanying drawings wherein:

FIG. 1 is a block diagram that illustrates a system including aprocessor and an implantable blood pump;

FIG. 2 is a flow diagram that illustrates a method of predicting anadverse event in a patient having the implantable blood pump of FIG. 1;

FIG. 3 is a block diagram the method of FIG. 2;

FIG. 4 is a graph that illustrates daily and cyclic changes inparameters including a flow value, pulsatility value, current value, andpump speed associated with the blood pump of FIG. 1 during use in theabsence of an onset of the adverse event;

FIG. 5 is a graph that illustrates changes in the parameters of FIG. 4during an adverse event;

FIG. 6 is four graphs that illustrate changes in the parameters of FIG.4;

FIG. 7 is four graphs that illustrate the adverse event as right heartfailure;

FIG. 8 is a flow chart that illustrates a method of predicting anadverse event in a patient having the blood pump of FIG. 1 which differsfrom the method of FIG. 2;

FIG. 9 is an equation that illustrates the method of FIG. 8;

FIG. 10 is a block diagram that illustrates the method of FIG. 8;

FIG. 11 is three graphs that illustrate an absence of an adverse event;

FIG. 12 is three graphs that illustrate the categories of information ofFIG. 11 and the presence of the adverse event;

FIG. 13 is a flow chart that illustrates a method of predicting anadverse event in a patient having the blood pump which differs from themethods of FIGS. 2 and 8;

FIG. 14 is a block diagram that illustrates the method of FIG. 13 usedto determine a flow trough index value;

FIG. 15 is a graph that illustrates a presence of a suction condition;and

FIG. 16 is two graphs that illustrate the presence of a suctioncondition and a determined flow trough index value exceeding apredetermined threshold range.

DETAILED DESCRIPTION

Before describing in detail exemplary embodiments, it is noted that theembodiments reside primarily in combinations of system components andprocessing steps related to an implantable blood pump. Accordingly, thesystem and process components have been represented where appropriate byconventional symbols in the drawings, showing only those specificdetails that are pertinent to understanding the embodiments of thepresent disclosure so as not to obscure the disclosure with details thatwill be readily apparent to those of ordinary skill in the art havingthe benefit of the description herein.

Referring now to the drawings in which like reference designators referto like elements, there is shown an exemplary system constructed inaccordance with the principles of the present disclosure and designatedgenerally as “10.” The system, and corresponding methods, provide aretrospective analysis of one or more blood pump parameters obtainedduring operation of the blood pump. Information gained from the analysismay be used to determine a patient's health condition, including whetherthe patient's condition is worsening over time. The system 10 maygenerate an alert when the patient's condition deviates from apredetermined threshold which may indicate one or more worseningconditions.

FIG. 1 is a block diagram of the system 10 including an implantableblood pump 12 in communication with a controller 14. The blood pump 12may be the HVAD® Pump or another mechanical circulatory support devicefully or partially implanted within the patient and having a movableelement, such as a rotor, configured to pump blood from the heart to therest of the body. The controller 14 includes a control circuit 16 formonitoring and controlling startup and subsequent operation of a motor18 implanted within the blood pump 12. The controller 14 may alsoinclude a processor 20, a memory 22, and an interface 24. The memory 22is configured to store information accessible by the processor 20including instructions 26 executable by the processor 20 and/or data 28that may be retrieved, manipulated, and/or stored by the processor 20.In particular, the processor 20 includes circuitry configured to carryout the steps discussed herein with respect to the methods. As such,reference to the system 10 executing steps of the methods is intended toinclude the processor 20.

In one example, the information stored by the processor 20 includesblood pump parameters determined by the system 10, such as an estimatedamount of blood flow through the blood pump 12, a flow trough value, anda flow pulsatility value. The amount of blood flow through the bloodpump 12 is computed in liters per minute, or another measuring unit,from the pump speed, the patient's hematocrit, and the pump current. Forexample, when the blood pump 12 is operating, the parameters arecaptured during a select timeframe, such as a sliding two-second window,of an estimated flow waveform and stored as log files. The minimum andthe maximum flow values are observed during the two-second window. Theflow trough value is the minimum flow value and the flow peak value isthe maximum flow value. The flow pulsatility value i.e., pulsatilityvalue, is the difference between the minimum and the maximum flowvalues. The flow pulsatility may be impacted by the patient'sconditions, for example, left ventricular contractility, right heartfunction, and left ventricular afterload. The timeframe may vary and theexemplary timeframe of two-seconds is provided in order to capture atleast one full cardiac cycle while accounting for a patient's heart rateas low as 30 BPM. The same process may be used to determine theparameters using real-time waveforms rather than the log files.

FIG. 2 is a flow chart of a method 30 of predicting an adverse event ina patient having an implantable blood pump, such as the blood pump 12,which is implemented by the system 10. The methods provided herein mayinclude additional steps, omit one or more steps, and/or may be providedin an order which differs from that which is shown. Further, the methodsmay be applied to log file data, i.e., trends in patient parameters,and/or real-time waveforms. The method 30 determines a patient's flowpulsatility and provides retrospective review of patient information,beyond daily and cyclic changes, which may reveal meaningful andrelatively severe changes in the flow pulsatility which correlate to theworsening of the patient's physiological state. Generally, the peak of aflow signal, i.e., a flow peak value, is used to trace the changes onthe patient's flow signals despite the presence of events such assuction, which are otherwise known to disturb flow trough andpulsatility values. In addition, a pulsatility peak value is determinedusing the flow peak value divided by the pump current to normalize theflow signal to the patient's running speed and power conditions.

In one configuration, the method begins at step 32 in which the system10 repeatedly or continuously determines the pulsatility value and theflow trough value. In step 34 the method 30 includes the system 10correlating the pulsatility value to the flow trough value determine theflow peak value. For example, the pulsatility value is added to the flowtrough value. In step 36, the determined flow peak value is divided bythe pump current to determine the pulsatility peak value. In order toassist in quantifying the pulsatility peak value, in step 38, the system10 proceeds to tracking a first moving average of the pulsatility peakvalue, and a corresponding standard deviation, which define a thresholdrange used to detect the onset of the adverse event.

In step 40, the system 10 continues with tracking a second movingaverage of the pulsatility peak value, the second moving average beingfaster than the first moving average. In one configuration, the firstmoving average is a twenty-four-hour moving average and the secondmoving average is approximately a two-hour duration; however, otherdurations are within the scope of the method 30. In step 42, the method30 includes the system 10 generating an alert when the second movingaverage deviates from the threshold range. The second moving averagedeviating from the threshold range and the corresponding alert indicatea notable change in the patient's pulsatility relative to a previoustime period.

The alert may be audible, visual, vibratory, or the like, and may betransmitted in real-time to the controller 14 or a remote location forclinician review and/or provided in a report. One or more instances ofthe alert occurring over a time period may be recorded, and based on thealert occurrences, the system 10 may determine a risk factor associatedwith a predicted onset of the adverse event. For example, the riskfactor may be a one to ten scale with the likelihood of the adverseevent occurring increasing in from one to ten. The risk factor may beused to classify changes in the patient's physiological state among aranking system, such as a one to ten scale with ten being a relativelysevere change in the patient's physiological state relative to aprevious time period, signaling the need for immediate medicalintervention.

FIG. 3 the method 30 executed as an algorithm including the first movingaverage is shown as a waveform “FMA”. FIG. 4 is a graph depicting dailyand cyclic changes in the flow value, pulsatility value, current value,and pump speed associated with the blood pump 12 during use in theabsence of an onset of the adverse event. The graph is displayed aspatient log files. FIG. 5 is a graph depicting changes the parameters ofFIG. 4 during an adverse event. The changes in the pulsatility value arehighlighted and analyzed through retrospective review to determinewhether the patient's condition is worsening over time.

FIG. 6 depicts four graphs showing the system 10 continuously orrepeatedly running to tracking the pulsatility peak value, such asthrough the algorithm. Graph “G1” depicts changes in the flow value,pulsatility value, current value, and pump speed associated with theblood pump 12. Graph “G2” depicts the flow peak value “FP” plottedrelative to the flow trough value “FT” and graph “G3” depicts thecurrent value. Graph “G4” depicts the threshold range “T” defined by thefirst moving average and the associated standard deviation. The secondmoving average “SMA” is plotted relative to the threshold range and adeviation from the threshold range indicates the notable change whichprompts the alert. The deviation may be above or below the thresholdrange. In other words, the notable change is indicated when the secondmoving average crosses over the threshold range, whether above or below.The deviation amount and/or frequency may be used to quantify changes inthe patient's homeostasis and/or hemodynamics which may be used as arisk factor or indicator of an onset of the adverse event. For example,FIG. 7 depicts 4 graphs including the parameters of FIG. 6 illustratingthe adverse event as right heart failure. The deviation of the secondmoving average from the threshold range is designated as “AE”.

FIG. 8 is a flow chart of another method 44 of predicting an adverseevent in a patient having the blood pump 12 which is implemented by thesystem 10. The method 44 provides retrospective review of patientinformation which may reveal that sustained periods of relativelyhigh-pulsatility and low flow trough measured with respect to standardpulsatility and flow for the patient correspond to the deterioration ofpatient conditions and an onset of an adverse event. As such, the method44 is configured to target sustained periods of relativelyhigh-pulsatility and low flow trough values in individual patients.

In one configuration, the method 44 begins at step 46 and proceeds tostep 48 including the system 10 tracking an average pulsatility valueassociated with the blood pump 12 during operation. The system 10 mayoperate in terms of an algorithm with the blood pump parameters beingtracked over a duration expressed as a window size of days, week, ormonths. The average pulsatility value may be correlated to a scalingcoefficient. In one example, the average pulsatility value is multipliedby the scaling coefficient of 100.

In step 50, the system 10 proceeds to tracking one or more parametersassociated with the blood pump 12 including an average flow troughvalue, an average flow value, and a standard flow trough deviationvalue. The standard flow trough deviation value is measured with respectto the average flow trough value and is correlated to an offset value.The offset value is an added constant configured to prevent falseidentification of the periods of the high-pulsatility and low flowtrough which may otherwise be affected by negative flow conditionsabsent the offset.

In step 52, the method 44 includes correlating the average pulsatilityvalue to the parameters. For example, FIG. 9 depicts an equationincluding the average pulsatility value expressed as a numerator and theparameters being the average flow trough value added to the offset valueand multiplied by the average flow value and the standard flow troughdeviation value. In step 54, the method 44 includes determining anadverse event index value using the correlated average pulsatility valuerelative to the parameters. In other words, the equation is used todetermine the adverse event index value which may be referred to as apulsatility-trough indicator.

Proceeding to step 56, the method 44 compares the adverse event indexvalue to a predetermined threshold range. In step 58, the system 10generates an alert when the compared adverse event index value deviatesfrom the predetermined threshold range. The alert includes thecharacteristics described above with respect to the method 30. Theadverse event index value deviating from the predetermined thresholdrange indicates a presence of the adverse event, for example, a periodof high-pulsatility and low flow trough. FIG. 10 is a block diagramdepicting the method 44 used to determine the adverse event index value.

FIG. 11 is three graphs of sample data in the form of log file data. Thegraph “G1” depicts the average pulsatility value and the parametersassociated with the blood pump expressed as waveforms. Graph “G2”depicts the adverse event index value expressed as a waveform “W” andpredetermined threshold value “PT” over a twelve-hour window. Thepredetermined threshold “PT” is depicted as being below the waveformwhich indicates an absence of the tracked condition, i.e., the adverseevent or period of high-pulsatility and low flow trough. The graph “G3”depicts the Boolean output “T” that indicates whether the index isgreater than the predetermined threshold.

FIG. 12 is three graphs of sample data in the form of log file datadisplaying the categories of information shown in the graphs of FIG. 11and designated as “G4”, “G5”, and “G6”. The graph G4 provides the logfile data of the parameters expressed as waveforms, whereas the graph G5depicts the waveform over a twelve-hour window during which the waveformdeviates from the predetermined threshold “PT” at the regions marked“D1” and “D2,” which are indicative of the tracked condition. Inparticular FIG. 12 depicts the waveform crossing the predeterminedthreshold as indicative of the presence of the tracked condition. Inother words, the adverse event index value exceeding the predeterminedthreshold range is expressed as an abnormal feature of the waveform. Thegraph “G6” depicts the Boolean output “T” that indicates whether theindex is greater than the predetermined threshold.

The system 10 may be configured to determine one or more of the adverseevent index values during one or more time periods, compare the adverseevent index values to each other, and based on the compared adverseevent index values, classify a patient's physiological state among aranking system. The ranking system may be of various types, for examplethe one to ten scale discussed above.

FIG. 13 is a flow chart of another method 60 of predicting an adverseevent in a patient having the blood pump 12 which is implemented by thesystem 10. The adverse event may be a suction event characterized byrelatively sharp negative deflections in estimated flow and powerthrough the blood pump 12 relative to a patient's standard state. Themethod 60 provides retrospective review of patient information which mayreveal meaningful and relatively severe changes in a patient's flow,e.g., flow trough, corresponding to suction events. Such changes can bequantified to assess conditions surrounding low flow and a suctionburden. Generally, the method 60 includes determining a flow troughindex value for more than one log file data points by taking the ratioof a standard deviation of a trough value to an average of the troughvalue.

In one configuration, the method 60 begins at step 62 and proceeds tostep 64 including the system 10 identifying a flow trough valueassociated with the blood pump 12 during use. The flow trough value maybe a minimum flow value relative to other flow values obtained during aselect duration or window of blood flow through the blood pump 12 duringuse. In step 66, the method 60 includes comparing the flow trough valueto a standard deviation flow value and an average flow value alsodetermined during the duration. In step 68, the system 10 determines aflow trough index value using the compared flow trough value to thestandard deviation flow value and the average flow value. In particular,the standard deviation flow value is divided by the average flow valueto determine the flow trough index value. In step 70, the system 10generates an alert when the flow trough index value deviates from apredetermined threshold range which indicates a presence of a suctioncondition. The alert may include the characteristics provided above withrespect to the method 30. The predetermined threshold may be customizedby a clinician based on how aggressively the clinician intends to trackand assess the adverse event, such as the suction conditions.

FIG. 14 is a block diagram depicting the method 60 used to determine theflow trough index value. As depicted, prior to determining the flowtrough value, the system 10 is configured to determine a presence of anegative flow trough value relative to a flow scale. The flow scale maybe a select flow threshold for the particular patient. When the negativeflow trough value is present, the flow trough value is correlated to aconstant which is an offset value equal to a magnitude of a lowesttrough value. In other words, the flow trough value is offset by theconstant. The flow trough value which has been offset is correlated tothe standard deviation flow value and the average flow value todetermine the flow trough index value. Thereafter, the flow trough indexvalue is multiplied by a constant, e.g., an offset value or correctivefactor.

The flow trough index value may be used to quantify a suction prevalenceassociated with the blood pump 12. For example, the system 10 may beconfigured to determine more than one flow trough index value, and basedon the flow trough index values which have been determined, quantify asuction prevalence associated with the blood pump. The suctionprevalence is a predicted frequency or likelihood of the patient toexperience a suction condition and may be used to classify a patient'sphysiological state among a ranking system. The ranking system mayindicate a worsening of the patient's condition, as discussed above.

FIG. 15 is a graph depicting changes in the flow value, pulsatilityvalue, current value, and pump speed associated with the blood pump 12during a suction condition at region “S” determined by the method 66.FIG. 16 is a graph “G1” of exemplary log file data including the flowvalue, pulsatility value, current value, and pump speed associated withthe blood pump 12. The flow value and the pulsatility value deviate fromthe predetermined threshold at region “S”. The graph “G2” corresponds tothe graph G1 and depicts an exemplary trough index value determinedusing the method 66 and shown as an output which exceeds thepredetermined threshold range “PT” at region S.

It should be understood that various aspects disclosed herein may becombined in different combinations than the combinations specificallypresented in the description and accompanying drawings. It should alsobe understood that, depending on the example, certain acts or events ofany of the processes or methods described herein may be performed in adifferent sequence, may be added, merged, or left out altogether (e.g.,all described acts or events may not be necessary to carry out thetechniques). In addition, while certain aspects of this disclosure aredescribed as being performed by a single module or unit for purposes ofclarity, it should be understood that the techniques of this disclosuremay be performed by a combination of units or modules associated with,for example, a medical device.

In one or more examples, the described techniques may be implemented inhardware, software, firmware, or any combination thereof. If implementedin software, the functions may be stored as one or more instructions orcode on a computer-readable medium and executed by a hardware-basedprocessing unit. Computer-readable media may include non-transitorycomputer-readable media, which corresponds to a tangible medium such asdata storage media (e.g., RAM, ROM, EEPROM, flash memory, or any othermedium that can be used to store desired program code in the form ofinstructions or data structures and that can be accessed by a computer).

Instructions may be executed by one or more processors, such as one ormore digital signal processors (DSPs), general purpose microprocessors,application specific integrated circuits (ASICs), field programmablelogic arrays (FPGAs), or other equivalent integrated or discrete logiccircuitry. Accordingly, the term “processor” as used herein may refer toany of the foregoing structure or any other physical structure suitablefor implementation of the described techniques. Also, the techniquescould be fully implemented in one or more circuits or logic elements.

It will be appreciated by persons skilled in the art that the presentinvention is not limited to what has been particularly shown anddescribed herein above. In addition, unless mention was made above tothe contrary, it should be noted that all of the accompanying drawingsare not to scale. A variety of modifications and variations are possiblein light of the above teachings without departing from the scope andspirit of the invention, which is limited only by the following claims.

What is claimed is:
 1. A method of predicting an adverse event in apatient having an implantable blood pump, the method comprising:correlating a pulsatility value to a flow trough value associated withthe blood pump to determine a flow peak value; dividing the determinedflow peak value by a pump current to determine a pulsatility peak value;tracking a first moving average of the pulsatility peak value, the firstmoving average defining a threshold range; tracking a second movingaverage of the pulsatility peak value, the second moving average beingfaster than the first moving average; and generating an alert when thesecond moving average deviates from the threshold range.
 2. The methodof claim 1, further comprising recording a plurality of alertoccurrences over a time period, and based on the plurality of alertoccurrences, determining a risk factor associated with a predicted onsetof the adverse event.
 3. The method of claim 2, further comprising,based on the determined risk factor, automatically classifying apatient's physiological state among a ranking system.
 4. The method ofclaim 1, further comprising determining a standard deviation of thefirst moving average, the first moving average and the standarddeviation defining the threshold range.
 5. The method of claim 1,wherein the first moving average is a twenty-four-hour moving averageand the second moving average is approximately a two-hour duration.
 6. Asystem of predicting an adverse event in a patient having an implantableblood pump, the system comprising: the blood pump; and a processor incommunication with the blood pump, the processor having processcircuitry configured to: correlate a pulsatility value to a flow troughvalue associated with the blood pump to determine a flow peak value;divide the determined flow peak value by a pump current to determine apulsatility peak value; track a first moving average of the pulsatilitypeak value, the first moving average defining a threshold range; track asecond moving average of the pulsatility peak value, the second movingaverage being faster than the first moving average; and generate analert when the second moving average deviates from the threshold range.7. The system of claim 6, wherein the process circuitry is configured torecord a plurality of alert occurrences over a time period, and based onthe plurality of alert occurrences, determine a risk factor associatedwith a predicted onset of the adverse event.
 8. A method of predictingan adverse event in a patient having an implantable blood pump, themethod comprising: tracking an average pulsatility value associated withthe blood pump; tracking a plurality of parameters associated with theblood pump, the plurality of parameters including an average flow troughvalue, an average flow value, and a standard flow trough deviationvalue, the standard flow trough deviation value being measured withrespect to the average flow trough value; correlating the averagepulsatility value to the plurality of parameters; determining an adverseevent index value using the correlated average pulsatility valuerelative to the plurality of parameters; comparing the adverse eventindex value to a predetermined threshold range; and generating an alertwhen the compared adverse event index value deviates from thepredetermined threshold range.
 9. The method of claim 8, furthercomprising correlating the average pulsatility value to a scalingcoefficient.
 10. The method of claim 8, further comprising correlatingthe standard flow trough deviation value to an offset value.
 11. Themethod of claim 8, further comprising determining a plurality of adverseevent index values during a plurality of time periods, comparing theplurality of adverse event index values to each other, and based on thecompared plurality of adverse event index values, classifying apatient's physiological state among a ranking system.
 12. The method ofclaim 8, wherein the average pulsatility value and the plurality ofparameters associated with the blood pump are expressed as a waveform,and the adverse event index value exceeding the predetermined thresholdrange is expressed as an abnormal feature of the waveform.
 13. A systemof predicting an adverse event in a patient having an implantable bloodpump, the system comprising: the blood pump; and a processor incommunication with the blood pump, the processor having processcircuitry configured to: track an average pulsatility value associatedwith the blood pump; track a plurality of parameters associated with theblood pump, the plurality of parameters including an average flow troughvalue, an average flow value, and a standard flow trough deviationvalue, the standard flow trough deviation value being measured withrespect to the average flow value; correlate the average pulsatilityvalue to the plurality of parameters; determine an adverse event indexvalue using the correlated average pulsatility value relative to theplurality of parameters; compare the adverse event index value to apredetermined threshold range; and generate an alert when the comparedadverse event index value deviates from the predetermined thresholdrange.
 14. A method of predicting an adverse event in a patient havingan implantable blood pump, the method comprising: identifying a flowtrough value associated with the blood pump during use; comparing theflow trough value to a standard deviation flow value and an average flowvalue; determining a flow trough index value using the compared flowtrough value to the standard deviation flow value and the average flowvalue; and generating an alert when the flow trough index value deviatesfrom a predetermined threshold range.
 15. The method of claim 14,further comprising, based on the determined flow trough index value,quantifying a suction prevalence associated with the blood pump.
 16. Themethod of claim 14, further comprising determining a plurality of flowtrough index values, and based on the determined plurality of flowtrough index values, quantifying a suction prevalence associated withthe blood pump.
 17. The method of claim 16, further comprising, based onthe suction prevalence, classifying a patient's physiological stateamong a ranking system.
 18. The method of claim 14, further comprising:determining a presence of a negative flow trough value relative to aflow scale, if the negative flow trough value is present, correlatingthe flow trough value to a constant, and following correlating the flowtrough value to the constant, determining the flow trough index value.19. The method of claim 18, further comprising multiplying the flowtrough index value by a corrective factor.
 20. The method of claim 14,further comprising dividing the standard deviation flow value and theaverage flow value.
 21. A system of predicting an adverse event in apatient having an implantable blood pump, the system comprising: theblood pump; and a processor in communication with the blood pump, theprocessor having process circuitry configured to: identify a flow troughvalue associated with the blood pump during use; compare the flow troughvalue to a standard deviation flow value and an average flow value;determine a flow trough index value using the compared flow trough valueto the standard deviation flow value and the average flow value; andgenerate an alert when the flow trough index value deviates from apredetermined threshold range.